Representing digital images based on one or more characteristics is required in a variety of fields or scenarios. Detecting and/or identifying similarities between digital images is of great importance in numerous fields and applications in various industries. For example, when searching a database for a set of images that share one or more attributes, a similarity of images in the database may be determined or measured with respect to a reference image. Images may be represented based on an attribute or characteristic in order to accomplish such and other tasks.
For example, provided with a reference image, current systems and methods use various methods to determine one or more parameters or attributes of the input image (e.g., a color distribution histogram, color saturation etc.) and search for similar images in a repository of images by searching for images having the same (or similar) parameters or attributes.
However, current systems and methods suffer from a number of drawbacks. For example, determining attributes of an input image and of images in a repository may be time consuming and/or require considerable computational resources. Moreover, when searching for similar images based on attributes such as color distribution, current methods and systems often produce inadequate results, for example, based on a color distribution, an image of a blue sky may be considered similar to an image of a lake or an ocean.